The Noise Clinic: a Blind Image Denoising Algorithm
Marc Lebrun, Miguel Colom, Jean-Michel Morel
→ BibTeX
    title   = {{The Noise Clinic: a Blind Image Denoising Algorithm}},
    author  = {Lebrun, Marc and Colom, Miguel and Morel, Jean-Michel},
    journal = {{Image Processing On Line}},
    volume  = {5},
    pages   = {1--54},
    year    = {2015},
    doi     = {10.5201/ipol.2015.125},
% if your bibliography style doesn't support doi fields:
    note    = {\url{}}
Marc Lebrun, Miguel Colom, and Jean-Michel Morel, The Noise Clinic: a Blind Image Denoising Algorithm, Image Processing On Line, 5 (2015), pp. 1–54.

Communicated by Jacques Froment
Demo edited by Miguel Colom


This paper describes the complete implementation of a blind image algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD) noise model. In a second step, the image is denoised by a multiscale adaptation of the Non-local Bayes denoising method. We focus here on a careful analysis of the denoising step and present a detailed discussion of the influence of its parameters. Extensive commented tests of the blind denoising algorithm are presented, on real JPEG images and scans of old photographs.